{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pileups \\#2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# downloading Hi-C data: beware, it is 21Gb big!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T16:42:19.780310Z",
     "start_time": "2019-03-08T16:36:08.317323Z"
    }
   },
   "outputs": [],
   "source": [
    "%%bash\n",
    "mkdir -p /tmp/pileup-example/\n",
    "wget https://data.4dnucleome.org/files-processed/4DNFIB59T7NN/@@download/4DNFIB59T7NN.mcool -qO /tmp/pileup-example/HFFc6_DpnII.mcool\n",
    "wget https://www.encodeproject.org/files/ENCFF401MQL/@@download/ENCFF401MQL.bed.gz -qO /tmp/pileup-example/HFF_Myc_CTCF_encode.conservative_idr_peaks.bed.gz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T20:30:38.189593Z",
     "start_time": "2019-03-08T20:30:38.155202Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib\n",
    "import matplotlib.gridspec\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "plt.rcParams['pdf.fonttype'] = 'truetype'\n",
    "plt.rcParams['svg.fonttype'] = 'none' # No text as paths. Assume font installed.\n",
    "\n",
    "plt.rcParams['font.serif'] = ['Times New Roman']\n",
    "plt.rcParams['font.sans-serif'] = ['Arial']\n",
    "plt.rcParams['font.size'] = 14\n",
    "plt.rcParams['font.family'] = 'sans-serif'\n",
    "plt.rcParams['text.usetex'] = False\n",
    "\n",
    "%config Completer.use_jedi = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T19:48:50.240844Z",
     "start_time": "2019-03-08T19:48:49.382059Z"
    }
   },
   "outputs": [],
   "source": [
    "import bioframe\n",
    "import cooler\n",
    "import cooltools\n",
    "import cooltools.expected"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T19:48:50.950553Z",
     "start_time": "2019-03-08T19:48:50.242740Z"
    }
   },
   "outputs": [],
   "source": [
    "import bioframe\n",
    "\n",
    "chromsizes = bioframe.fetch_chromsizes('hg38')\n",
    "cens = bioframe.fetch_centromeres('hg38')\n",
    "cens.set_index('chrom', inplace=True)\n",
    "cens = cens.mid\n",
    "\n",
    "GOOD_CHROMS = list(chromsizes.index[:23])\n",
    "\n",
    "arms = [arm \n",
    "        for chrom in GOOD_CHROMS\n",
    "        for arm in ((chrom, 0, cens.get(chrom,0)), \n",
    "                    (chrom, cens.get(chrom,0), chromsizes.get(chrom,0)))\n",
    "]\n",
    "arms = pd.DataFrame(arms, columns=['chrom','start', 'end'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T20:26:41.310321Z",
     "start_time": "2019-03-08T20:26:41.250975Z"
    }
   },
   "outputs": [],
   "source": [
    "BINSIZE = 2000\n",
    "clr=cooler.Cooler(f'/tmp/pileup-example/HFFc6_DpnII.mcool::/resolutions/{BINSIZE}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T19:54:40.197503Z",
     "start_time": "2019-03-08T19:49:20.246430Z"
    }
   },
   "outputs": [],
   "source": [
    "import multiprocess\n",
    "\n",
    "with multiprocess.Pool(20) as pool:\n",
    "    expected = cooltools.expected.diagsum(\n",
    "        clr, \n",
    "        list(arms.itertuples(index=False,name=None)), \n",
    "        transforms={\n",
    "            'balanced': lambda p: p['count'] * p['weight1'] * p['weight2']\n",
    "        },\n",
    "    map=pool.map\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T20:10:04.899097Z",
     "start_time": "2019-03-08T20:10:04.058689Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/golobor/miniconda3/lib/python3.7/site-packages/ipykernel_launcher.py:5: FutureWarning: Interpreting tuple 'by' as a list of keys, rather than a single key. Use 'by=[...]' instead of 'by=(...)'. In the future, a tuple will always mean a single key.\n",
      "  \"\"\"\n"
     ]
    }
   ],
   "source": [
    "expected_df = pd.concat([\n",
    "    exp.reset_index().assign(chrom=reg[0], start=reg[1], end=reg[2])\n",
    "    for reg, exp in expected.items()])\n",
    "\n",
    "expected_df = expected_df.groupby(('chrom','diag')).aggregate({\n",
    "    'n_valid':'sum',\n",
    "    'count.sum':'sum',\n",
    "    'balanced.sum':'sum'}).reset_index()\n",
    "\n",
    "expected_df['balanced.avg'] = expected_df['balanced.sum'] / expected_df['n_valid']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T19:57:22.957877Z",
     "start_time": "2019-03-08T19:57:19.569555Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/golobor/miniconda3/lib/python3.7/site-packages/pybedtools/bedtool.py:3439: FutureWarning: read_table is deprecated, use read_csv instead, passing sep='\\t'.\n",
      "  return pandas.read_table(self.fn, *args, **kwargs)\n"
     ]
    }
   ],
   "source": [
    "import pybedtools\n",
    "ctcf_peaks = pybedtools.BedTool('/tmp/pileup-example/HFF_Myc_CTCF_encode.conservative_idr_peaks.bed.gz').sort()\n",
    "ctcf_motifs = pybedtools.BedTool('./encode_motifs.hg38.ctcf_known1.liftover.bed.gz').sort()\n",
    "ctcf_motifs_w_peaks = ctcf_motifs.intersect(ctcf_peaks).to_dataframe()\n",
    "ctcf_motifs_w_peaks['mid'] = (ctcf_motifs_w_peaks.start + ctcf_motifs_w_peaks.end) / 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T19:57:23.185073Z",
     "start_time": "2019-03-08T19:57:22.960768Z"
    }
   },
   "outputs": [],
   "source": [
    "import cooltools.snipping\n",
    "\n",
    "WINDOW_HALF_SIZE = 100000\n",
    "snipping_windows = cooltools.snipping.make_bin_aligned_windows(\n",
    "    BINSIZE,\n",
    "    ctcf_motifs_w_peaks.chrom.values,\n",
    "    ctcf_motifs_w_peaks.mid.values,\n",
    "    WINDOW_HALF_SIZE\n",
    ")\n",
    "\n",
    "snipping_windows = cooltools.snipping.assign_regions(\n",
    "    snipping_windows, \n",
    "    list(arms.itertuples(index=False,name=None)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T20:23:50.678845Z",
     "start_time": "2019-03-08T20:23:09.642661Z"
    }
   },
   "outputs": [],
   "source": [
    "# ICCF_snipper = cooltools.snipping.CoolerSnipper(clr)\n",
    "\n",
    "# with multiprocess.Pool(20) as pool:\n",
    "#     ICCF_pile = cooltools.snipping.pileup(\n",
    "#             snipping_windows, \n",
    "#             ICCF_snipper.select, ICCF_snipper.snip,\n",
    "#             map=pool.map)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T20:15:16.324828Z",
     "start_time": "2019-03-08T20:14:04.877112Z"
    }
   },
   "outputs": [],
   "source": [
    "oe_snipper = cooltools.snipping.ObsExpSnipper(clr, expected_df)\n",
    "\n",
    "with multiprocess.Pool(20) as pool:\n",
    "    oe_pile = cooltools.snipping.pileup(\n",
    "            snipping_windows, \n",
    "            oe_snipper.select, oe_snipper.snip,\n",
    "            map=pool.map)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T20:29:40.832580Z",
     "start_time": "2019-03-08T20:29:38.274300Z"
    }
   },
   "outputs": [],
   "source": [
    "collapsed_pile_plus = np.nanmean(\n",
    "    oe_pile[:, :, ctcf_motifs_w_peaks.strand=='+'], axis=2\n",
    ")\n",
    "collapsed_pile_minus = np.nanmean(\n",
    "    oe_pile[:, :, ctcf_motifs_w_peaks.strand=='-'], axis=2\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-03-08T20:30:41.115095Z",
     "start_time": "2019-03-08T20:30:40.898884Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'relative position, kbp')"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(\n",
    "    np.log2(collapsed_pile_plus), \n",
    "    vmax = 0.5, \n",
    "    vmin = -0.5,\n",
    "    cmap='coolwarm')\n",
    "plt.colorbar(label = 'log2 mean obs/exp')\n",
    "ticks_pixels = np.linspace(0, WINDOW_HALF_SIZE*2//BINSIZE,5)\n",
    "ticks_kbp = ((ticks-ticks[-1]/2)*BINSIZE//1000).astype(int)\n",
    "plt.xticks(ticks_pixels, ticks_kbp)\n",
    "plt.yticks(ticks_pixels, ticks_kbp)\n",
    "plt.xlabel('relative position, kbp')\n",
    "plt.ylabel('relative position, kbp')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.5"
  },
  "nav_menu": {},
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": false,
   "sideBar": false,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": false,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
